a1 University of Hawaiʻi at Mānoa
a2 New Zealand Institute of Language Brain and Behaviour, University of Canterbury
An increasing number of sociolinguists are using mixed effects models, models which allow for the inclusion of both fixed and random predicting variables. In most analyses, random effect intercepts are treated as a by-product of the model; they are viewed simply as a way to fit a more accurate model. This paper presents additional uses for random effect intercepts within the context of two case studies. Specifically, this paper demonstrates how random intercepts can be exploited to assist studies of speaker style and identity and to normalize for vocal tract size within certain linguistic environments. We argue that, in addition to adopting mixed effect modeling more generally, sociolinguists should view random intercepts as a potential tool during analysis.
This paper has benefited from helpful comments from Daniel Ezra Johnson, Rena Torres Cacoullos, and three anonymous reviewers. We would also like to thank Sali Tagliamonte and the audience of the workshop on using statistical tools to explain linguistic variation at New Ways of Analyzing Variation (NWAV) 38.